The International Mouse Phenotyping Consortium: past and future perspectives on mouse phenotyping

Determining the function of all mammalian genes remains a major challenge for the biomedical science community in the 21st century. The goal of the International Mouse Phenotyping Consortium (IMPC) over the next 10?years is to undertake broad-based phenotyping of 20,000 mouse genes, providing an unprecedented insight into mammalian gene function. This short article explores the drivers for large-scale mouse phenotyping and provides an overview of the aims and processes involved in IMPC mouse production and phenotyping.     

Hunting human disease genes: lessons from the past, challenges for the future

The concept that a specific alteration in an individual’s DNA can result in disease is central to our notion of molecular medicine. The molecular basis of more than 3,500 Mendelian disorders has now been identified. In contrast, the identification of genes for common disease has been much more challenging. We discuss historical and contemporary approaches to disease gene identification, focusing on novel opportunities such as the use of population extremes and the identification of rare variants. While our ability to sequence DNA has advanced dramatically, assigning function to a given sequence change remains a major challenge, highlighting the need for both bioinformatics and functional approaches to appropriately interpret these data. We review progress in mapping and identifying human disease genes and discuss future challenges and opportunities for the field.     

Comparative study of apoptosis-related gene loci in human, mouse and rat genomes

Many genes are involved in mammalian cell apoptosis pathway. These apoptosis genes often contain characteristic functional domains, and can be classified into at least 15 functional groups, according to previous reports. Using an integrated bioinformatics platform for motif or domain search from three public mammalian proteomes (International Protein Index database for human, mouse, and rat), we systematically cataloged all of the proteins involved in mammalian apoptosis pathway. By localizing those proteins onto the genomes, we obtained a gene locus centric apoptosis gene catalog for human, mouse and rat.Further phylogenetic analysis showed that most of the apoptosis related gene loci are conserved among these three mammals. Interestingly, about one-third of apoptosis gene loci form gene clusters on mammal chromosomes, and exist in the three species, which indicated that mammalian apoptosis gene orders are also conserved. In addition, some tandem duplicated gene loci were revealed by comparing gene loci clusters in the three species. All data produced in this work were stored in a relational database and may be viewed at http://pcas.cbi.pku.edu.cn/database/apd.php.     

New routes for transgenesis of the mouse

Transgenesis refers to the molecular genetic techniques for directing specific insertions, deletions and point mutations in the genome of germ cells in order to create genetically modified organisms (GMO). Genetic modification is becoming more practicable, efficient and predictable with the development and use of a variety of cell and molecular biology tools and DNA sequencing technologies. A collection of plasmidial and viral vectors, cell-type specific promoters, positive and negative selectable markers, reporter genes, drug-inducible Cre-loxP and Flp/FRT recombinase systems are available which ensure efficient transgenesis in the mouse. The technologies for the insertion and removal of genes by homologous-directed recombination in embryonic stem cells (ES) and generation of targeted gain- and loss-of function alleles have allowed the creation of thousands of mouse models of a variety of diseases. The engineered zinc finger nucleases (ZFNs) and small hairpin RNA-expressing constructs are novel tools with useful properties for gene knockout free of ES manipulation. In this review we briefly outline the different approaches and technologies for transgenesis as well as their advantages and disadvantages. We also present an overview on how the novel integrative mouse and human genomic databases and bioinformatics approaches have been used to understand genotype-phenotype relationships of hundreds of mutated and candidate disease genes in mouse models. The updating and continued improvements of the genomic technologies will eventually help us to unraveling the biological and pathological processes in such a way that they can be translated more efficiently from mouse to human and vise-versa.     

Automated construction and testing of multi-locus gene-gene associations

It has been argued that the missing heritability in common diseases may be in part due to rare variants and gene-gene effects. Haplotype analyses provide more power for rare variants and joint analyses across genes can address multi-gene effects. Currently, methods are lacking to perform joint multi-locus association analyses across more than one gene/region. Here, we present a haplotype-mining gene-gene analysis method, which considers multi-locus data for two genes/regions simultaneously. This approach extends our single region haplotype-mining algorithm, hapConstructor, to two genes/regions. It allows construction of multi-locus SNP sets at both genes and tests joint gene-gene effects and interactions between single variants or haplotype combinations. A Monte Carlo framework is used to provide statistical significance assessment of the joint and interaction statistics, thus the method can also be used with related individuals. This tool provides a flexible data-mining approach to identifying gene-gene effects that otherwise is currently unavailable. AVAILABILITY: http://bioinformatics.med.utah.edu/Genie/hapConstructor.html.     

The emerging role for rat models in gene discovery

Rat models have been used for many decades to study physiological and pathophysiological mechanisms. Prior to the release of the rat genome and new technologies for targeting gene manipulation, the rat had been the underdog in the genomics era, despite the abundance of physiological data compared to the mouse. The overarching goal of biomedical research is to improve health and advance medical science. Translating human disease gene discovery and validation in the rat, through the use of emerging technologies and integrated tools and databases, is providing power to understand the genetics, environmental influences, and biology of disease. In this review we briefly outline the rat models, bioinformatics tools, and technologies that are changing the landscape of translational research. The strategies used to translate disease traits to genes to function, and, ultimately, to improve human health is discussed. Finally, our perspective on how rat models will continue to positively impact biomedical research is provided.     

Genome-wide screening for gene function using RNAi in mammalian cells

Mammalian genome sequencing has identified numerous genes requiring functional annotation. The discovery that dsRNA can direct gene-specific silencing in both model organisms and mammalian cells through RNA interference (RNAi) has provided a platform for dissecting the function of independent genes. The generation of large-scale RNAi libraries targeting all predicted genes within mouse, rat and human cells, combined with the large number of cell-based assays, provides a unique opportunity to perform high-throughput genetics in these complex cell systems. Many different formats exist for the generation of genome-wide RNAi libraries for use in mammalian cells. Furthermore, the use of these libraries in either genetic screens or genetic selections allows for the identification of known and novel genes involved in complex cellular phenotypes and biological processes, some of which underpin human disease. In this review, we examine genome-wide RNAi libraries used in model organisms and mammalian cells and provide examples of how these information rich reagents can be used for determining gene function, discovering novel therapeutic targets and dissecting signalling pathways, cellular processes and complex phenotypes.     

Discovery of gene families and alternatively spliced variants by RecA-mediated cloning

Probing the functional complexity of the human genome will require new gene cloning techniques, not only to discover intraspecies gene homologs and interspecies gene orthologs, but also to identify alternatively spliced gene variants. We report homologous cDNA cloning methods that allow cloning of gene family members, genes from different species, and alternatively spliced gene variants. We cloned human 14-3-3 gene family members using DNA probes with as much as 35% sequence divergence, cloned alternatively spliced gene forms of Rad51D, and cloned a novel splice form of the human 14-3-3 theta gene with a unique expression pattern. Interspecies gene cloning was demonstrated for the mouse Rad51C and mouse beta-actin genes using human gene probes. The gene family cloning method is fast, efficient, and free from PCR errors; moreover, it exploits the abilities of RecA protein to pair homologous or partially homologous DNA sequences stably in kinetically trapped, multistranded DNA hybrids that can be used for subsequent gene clone enrichment.     

Systematic Identification and Characterization of Novel Human Skin-Associated Genes Encoding Membrane and Secreted Proteins

Through bioinformatics analyses of a human gene expression database representing 105 different tissues and cell types, we identified 687 skin-associated genes that are selectively and highly expressed in human skin. Over 50 of these represent uncharacterized genes not previously associated with skin and include a subset that encode novel secreted and plasma membrane proteins. The high levels of skin-associated expression for eight of these novel therapeutic target genes were confirmed by semi-quantitative real time PCR, western blot and immunohistochemical analyses of normal skin and skin-derived cell lines. Four of these are expressed specifically by epidermal keratinocytes; two that encode G-protein-coupled receptors (GPR87 and GPR115), and two that encode secreted proteins (WFDC5 and SERPINB7). Further analyses using cytokine-activated and terminally differentiated human primary keratinocytes or a panel of common inflammatory, autoimmune or malignant skin diseases revealed distinct patterns of regulation as well as disease associations that point to important roles in cutaneous homeostasis and disease. Some of these novel uncharacterized skin genes may represent potential biomarkers or drug targets for the development of future diagnostics or therapeutics.     

Evolution of the rat kallikrein gene family: Gene conversion leads to functional diversity

Summary Kallikrein-like simple serine proteases are encoded by closely related members of a gene family in several mammalian species. Molecular cloning and genomic Southern blot analysis after conventional and pulsed-field gel electrophoresis indicate that the rat kallikrein gene family comprises 15–20 members, probably closely linked at a single locus. Determination of the nucleotide sequences of the rGK-3,-4, and-6 genes here completes sequence data for a total of nine rat kallikrein family members. Comparison of the rat gene sequences to each other and to those of human and mouse kallikrein family genes reveals patterns of relatedness indicative of concerted evolution. Analysis of nucleotide sequence variants in kallikrein family members shows that most sequence variants are shared by multiple family members; the patterns of shared variants are complex and indicate multiple short gene conversions between family members. Sequence exchanges between family members generate novel assortments of variants in amino acid coding regions that may affect substrate specificity and thereby contribute to the diversity of enzyme activity. Furthermore, small sequence exchanges also may play a role in generating the diverse patterns of tissue-specific expression of rat family members. These analyses indicate an important role for gene conversion in the evolution of the functional diversity of these duplicated genes.     

Human genomics and microarrays: implications for the plastic surgeon

The Human Genome Project was launched in 1989 in an effort to sequence the entire span of human DNA. Although coding sequences are important in identifying mutations, the static order of DNA does not explain how a cell or organism may respond to normal and abnormal biological processes. By examining the mRNA content of a cell, researchers can determine which genes are being activated in response to a stimulus.Traditional methods in molecular biology generally work on a "one gene: one experiment" basis, which means that the throughput is very limited and the "whole picture" of gene function is hard to obtain. To study each of the 60,000 to 80,000 genes in the human genome under each biological circumstance is not practical. Recently, microarrays (also known as gene or DNA chips) have emerged; these allow for the simultaneous determination of expression for thousands of genes and analysis of genome-wide mRNA expression.The purpose of this article is twofold: first, to provide the clinical plastic surgeon with a working knowledge and understanding of the fields of genomics, microarrays, and bioinformatics and second, to present a case to illustrate how these technologies can be applied in the study of wound healing.     

Mitochondrial DNA Polymerase POLG1 Disease Mutations and Germline Variants Promote Tumorigenic Properties

Germline mutations in mitochondrial DNA polymerase gamma (POLG1) induce mitochondrial DNA (mtDNA) mutations, depletion, and decrease oxidative phosphorylation. Earlier, we identified somatic mutations in POLG1 and the contribution of these mutations in human cancer. However, a role for germline variations in POLG1 in human cancers is unknown. In this study, we examined a role for disease associated germline variants of POLG1, POLG1 gene expression, copy number variation and regulation in human cancers. We analyzed the mutations, expression and copy number variation in POLG1 in several cancer databases and validated the analyses in primary breast tumors and breast cancer cell lines. We discovered 5-aza-2''-deoxycytidine led epigenetic regulation of POLG1, mtDNA-encoded genes and increased mitochondrial respiration. We conducted comprehensive race based bioinformatics analyses of POLG1 gene in more than 33,000 European-Americans and 5,000 African-Americans. We identified a mitochondrial disease causing missense variation in polymerase domain of POLG1 protein at amino acid 1143 (E1143G) to be 25 times more prevalent in European-Americans (allele frequency 0.03777) when compared to African-American (allele frequency 0.00151) population. We identified T251I and P587L missense variations in exonuclease and linker region of POLG1 also to be more prevalent in European-Americans. Expression of these variants increased glucose consumption, decreased ATP production and increased matrigel invasion. Interestingly, conditional expression of these variants revealed that matrigel invasion properties conferred by these germline variants were reversible suggesting a role of epigenetic regulators. Indeed, we identified a set of miRNA whose expression was reversible after variant expression was turned off. Together, our studies demonstrate altered genetic and epigenetic regulation of POLG1 in human cancers and suggest a role for POLG1 germline variants in promoting tumorigenic properties.     

Gene expression data analysis

Microarrays are one of the latest breakthroughs in experimental molecular biology, which allow monitoring of gene expression for tens of thousands of genes in parallel and are already producing huge amounts of valuable data. Analysis and handling of such data is becoming one of the major bottlenecks in the utilization of the technology. The raw microarray data are images, which have to be transformed into gene expression matrices--tables where rows represent genes, columns represent various samples such as tissues or experimental conditions, and numbers in each cell characterize the expression level of the particular gene in the particular sample. These matrices have to be analyzed further, if any knowledge about the underlying biological processes is to be extracted. In this paper we concentrate on discussing bioinformatics methods used for such analysis. We briefly discuss supervised and unsupervised data analysis and its applications, such as predicting gene function classes and cancer classification. Then we discuss how the gene expression matrix can be used to predict putative regulatory signals in the genome sequences. In conclusion we discuss some possible future directions.     

A functional analysis of mouse models of cardiac disease through metabolic profiling

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function. Tools are needed for assessing the phenotypes of the many mouse models that are now being generated, where genes have been "knocked out," "knocked in," or mutated, so that gene expression can be understood in its biological context. Metabolic profiling of cardiac tissue through high resolution NMR spectroscopy in conjunction with multivariate statistics has been used to classify mouse models of cardiac disease. The data sets included metabolic profiles from mouse models of Duchenne muscular dystrophy, two models of cardiac arrhythmia, and one of cardiac hypertrophy. The metabolic profiles demonstrate that the strain background is an important component of the global metabolic phenotype of a mouse, providing insight into how a given gene deletion may result in very different responses in diverse populations. Despite these differences associated with strain, multivariate statistics were capable of separating each mouse model from its control strain, demonstrating that metabolic profiles could be generated for each disease. Thus, this approach is a rapid method of phenotyping mouse models of disease.     

Incorporating Non-Coding Annotations into Rare Variant Analysis

BackgroundThe success of collapsing methods which investigate the combined effect of rare variants on complex traits has so far been limited. The manner in which variants within a gene are selected prior to analysis has a crucial impact on this success, which has resulted in analyses conventionally filtering variants according to their consequence. This study investigates whether an alternative approach to filtering, using annotations from recently developed bioinformatics tools, can aid these types of analyses in comparison to conventional approaches.ConclusionIncorporating variant annotations from non-coding bioinformatics tools should prove to be a valuable asset for rare variant analyses in the future. Filtering by variant consequence is only possible in coding regions of the genome, whereas utilising non-coding bioinformatics annotations provides an opportunity to discover unknown causal variants in non-coding regions as well. This should allow studies to uncover a greater number of causal variants for complex traits and help elucidate their functional role in disease.